Holistic Inverse Rendering of Complex Facade via Aerial 3D Scanning

In this work, we use multi-view aerial images to reconstruct the geometry, lighting, and material of facades using neural signed distance fields (SDFs). Without the requirement of complex equipment, our method only takes simple RGB images captured by a drone as inputs to enable physically based and photorealistic novel-view rendering, relighting, and editing. However, a real-world facade usually has complex appearances ranging from diffuse rocks with subtle details to large-area glass windows with specular reflections, making it hard to attend to everything. As a result, previous methods can preserve the geometry details but fail to reconstruct smooth glass windows or verse vise. In order to address this challenge, we introduce three spatial- and semantic-adaptive optimization strategies, including a semantic regularization approach based on zero-shot segmentation techniques to improve material consistency, a frequency-aware geometry regularization to balance surface smoothness and details in different surfaces, and a visibility probe-based scheme to enable efficient modeling of the local lighting in large-scale outdoor environments. In addition, we capture a real-world facade aerial 3D scanning image set and corresponding point clouds for training and benchmarking. The experiment demonstrates the superior quality of our method on facade holistic inverse rendering, novel view synthesis, and scene editing compared to state-of-the-art baselines

I2^2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs

In this work, we present I$^2$-SDF, a new method for intrinsic indoor scene reconstruction and editing using differentiable Monte Carlo raytracing on neural signed distance fields (SDFs). Our holistic neural SDF-based framework jointly recovers the underlying shapes, incident radiance and materials from multi-view images. We introduce a novel bubble loss for fine-grained small objects and error-guided adaptive sampling scheme to largely improve the reconstruction quality on large-scale indoor scenes. Further, we propose to decompose the neural radiance field into spatially-varying material of the scene as a neural field through surface-based, differentiable Monte Carlo raytracing and emitter semantic segmentations, which enables physically based and photorealistic scene relighting and editing applications. Through a number of qualitative and quantitative experiments, we demonstrate the superior quality of our method on indoor scene reconstruction, novel view synthesis, and scene editing compared to state-of-the-art baselines.Comment: Accepted by CVPR 202

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Influences of Dietary Vitamin E, Selenium-Enriched Yeast, and Soy Isoflavone Supplementation on Growth Performance, Antioxidant Capacity, Carcass Traits, Meat Quality and Gut Microbiota in Finishing Pigs

This study investigated the effects of dietary compound antioxidants on growth performance, antioxidant capacity, carcass traits, meat quality, and gut microbiota in finishing pigs. A total of 36 barrows were randomly assigned to 2 treatments with 6 replicates. The pigs were fed with a basal diet (control) or the basal diet supplemented with 200 mg/kg vitamin E, 0.3 mg/kg selenium-enriched yeast, and 20 mg/kg soy isoflavone. Dietary compound antioxidants decreased the average daily feed intake (ADFI) and feed to gain ratio (F/G) at d 14–28 in finishing pigs (p p p Peptococcus at the genus level was increased and ileal Turicibacter_sp_H121 abundance at the species level was decreased by dietary compound antioxidants. Spearman analysis showed a significant negative correlation between the relative abundance of colonic Peptococcus and plasma MDA concentration and meat drip loss at 48 h. Collectively, dietary supplementation with compound antioxidants of vitamin E, selenium-enrich yeast, and soy isoflavone could improve feed efficiency and antioxidant capacity, and modify the backfat thickness and meat quality through modulation of the gut microbiota community

Monosymmetric Fe-N4 sites enabling durable proton exchange membrane fuel cell cathode by chemical vapor modification

Abstract The limited durability of metal-nitrogen-carbon electrocatalysts severely restricts their applicability for the oxygen reduction reaction in proton exchange membrane fuel cells. In this study, we employ the chemical vapor modification method to alter the configuration of active sites from FeN4 to the stable monosymmetric FeN2+N’2, along with enhancing the degree of graphitization in the carbon substrate. This improvement effectively addresses the challenges associated with Fe active center leaching caused by N-group protonation and free radicals attack due to the 2-electron oxygen reduction reaction. The electrocatalyst with neoteric active site exhibited excellent durability. During accelerated aging test, the electrocatalyst exhibited negligible decline in its half-wave potential even after undergoing 200,000 potential cycles. Furthermore, when subjected to operational conditions representative of fuel cell systems, the electrocatalyst displayed remarkable durability, sustaining stable performance for a duration exceeding 248 h. The significant improvement in durability provides highly valuable insights for the practical application of metal-nitrogen-carbon electrocatalysts